Lipid metabolism in cancer: New perspectives and emerging mechanisms

Broadfield, Lindsay A.; Pane, Antonino Alejandro; Talebi, Ali; Swinnen, Johannes V.; Fendt, Sarah-Maria

doi:10.1016/j.devcel.2021.04.013

Cited by 294 publications

(263 citation statements)

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“…There is evidence that lipid metabolic reprogramming can mediate resistance to anti-cancer agents including chemotherapy and targeted therapies including in breast, lung and prostate cancer cell lines and xenograft models [ 61 ]. Indeed, targeting altered metabolic lipid pathways with pharmacologic interventions has become an emerging anti-tumor strategy in several cancer types with currently 10 inhibitors being tested in clinical trials including TVB-2640 [ 62 ]. While in ovarian cancer overexpressed lipogenic enzymes are increasingly seen as potential therapeutic opportunity to inhibit cancer growth, peritoneal metastasis and/or overcome resistance to chemotherapy or anti-angiogenic therapy [ 61 , 63 , 64 ], our study is the first demonstration that the combined inhibition of PARP1 and FSAN represents an synergistic anti-proliferative combination strategy.…”

Section: Discussionmentioning

confidence: 99%

Molecular response to PARP1 inhibition in ovarian cancer cells as determined by mass spectrometry based proteomics

et al. 2021

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Background Poly (ADP)-ribose polymerase (PARP) inhibitors have entered routine clinical practice for the treatment of high-grade serous ovarian cancer (HGSOC), yet the molecular mechanisms underlying treatment response to PARP1 inhibition (PARP1i) are not fully understood. Methods Here, we used unbiased mass spectrometry based proteomics with data-driven protein network analysis to systematically characterize how HGSOC cells respond to PARP1i treatment. Results We found that PARP1i leads to pronounced proteomic changes in a diverse set of cellular processes in HGSOC cancer cells, consistent with transcript changes in an independent perturbation dataset. We interpret decreases in the levels of the pro-proliferative transcription factors SP1 and β-catenin and in growth factor signaling as reflecting the anti-proliferative effect of PARP1i; and the strong activation of pro-survival processes NF-κB signaling and lipid metabolism as PARPi-induced adaptive resistance mechanisms. Based on these observations, we nominate several protein targets for therapeutic inhibition in combination with PARP1i. When tested experimentally, the combination of PARPi with an inhibitor of fatty acid synthase (TVB-2640) has a 3-fold synergistic effect and is therefore of particular pre-clinical interest. Conclusion Our study improves the current understanding of PARP1 function, highlights the potential that the anti-tumor efficacy of PARP1i may not only rely on DNA damage repair mechanisms and informs on the rational design of PARP1i combination therapies in ovarian cancer.

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Section: Discussionmentioning

confidence: 99%

Molecular response to PARP1 inhibition in ovarian cancer cells as determined by mass spectrometry based proteomics

et al. 2021

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“…Studies have demonstrated that compared to traditional biomarkers, metabolic enzymes are superior as predictive biomarkers for various cancers (Dong et al, 2015;Xu et al, 2021). Metabolic alteration has wideranging effects, such as angiogenesis, metastasis, and immune escape, which has provided opportunities to solve immunotherapy resistance and poor clinical outcomes (Broadfield et al, 2021;Jones et al, 2021;Zanotelli et al, 2021). To date, the expression patterns of metabolic enzymes have been widely studied in different cancer types, such as liver, gastric, colorectal, breast, and prostate cancer (Lavorgna et al, 2018;Zinger et al, 2019;Rivello et al, 2020;Sun et al, 2020;Xu et al, 2020;Jiang et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

A Novel Integrated Metabolism-Immunity Gene Expression Model Predicts the Prognosis of Lung Adenocarcinoma Patients

Chen

Duan

et al. 2021

Front. Pharmacol.

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Background: Although multiple metabolic pathways are involved in the initiation, progression, and therapy of lung adenocarcinoma (LUAD), the tumor microenvironment (TME) for immune cell infiltration that is regulated by metabolic enzymes has not yet been characterized.Methods: 517 LUAD samples and 59 non-tumor samples were obtained from The Cancer Genome Atlas (TCGA) database as the training cohort. Kaplan-Meier analysis and Univariate Cox analysis were applied to screen the candidate metabolic enzymes for their role in relation to survival rate in LUAD patients. A prognostic metabolic enzyme signature, termed the metabolic gene risk score (MGRS), was established based on multivariate Cox proportional hazards regression analysis and was verified in an independent test cohort, GSE31210. In addition, we analyzed the immune cell infiltration characteristics in patients grouped by their Risk Score. Furthermore, the prognostic value of these four enzymes was verified in another independent cohort by immunohistochemistry and an optimized model of the metabolic-immune protein risk score (MIPRS) was constructed.Results: The MGRS model comprising 4 genes (TYMS, NME4, LDHA, and SMOX) was developed to classify patients into high-risk and low-risk groups. Patients with a high-risk score had a poor prognosis and exhibited activated carbon and nucleotide metabolism, both of which were associated with changes to TME immune cell infiltration characteristics. In addition, the optimized MIPRS model showed more accurate predictive power in prognosis of LUAD.Conclusion: Our study revealed an integrated metabolic enzyme signature as a reliable prognostic tool to accurately predict the prognosis of LUAD.

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“…Lipids possess several functions at cellular and organismal levels, making them critical for survival. Cellular FAs originate from exogenous uptake or de novo synthesis and are mainly used as substrates for FA oxidation and energy production or synthesis of TAGs and energy storage [ 1 ]. PGs, along with sterols and sphingolipids, are the main structural elements of biological membranes.…”

Section: The Role Of Lipids In Normal and Cancer Cell Physiologymentioning

confidence: 99%

“…Rapidly proliferating cancer cells reprogram their metabolism in order to meet increased energy and macromolecule requirements. To this end, lipidomic remodeling is a common feature of carcinogenesis (recently reviewed in [ 1 , 3 , 11 ]) ( Figure 1 ).…”

Section: The Role Of Lipids In Normal and Cancer Cell Physiologymentioning

confidence: 99%

Lipid Metabolism in Cancer: The Role of Acylglycerolphosphate Acyltransferases (AGPATs)

Karagiota

Chachami

Paraskeva

2022

Cancers

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Altered lipid metabolism is an emerging hallmark of aggressive tumors, as rapidly proliferating cancer cells reprogram fatty acid (FA) uptake, synthesis, storage, and usage to meet their increased energy demands. Central to these adaptive changes, is the conversion of excess FA to neutral triacylglycerides (TAG) and their storage in lipid droplets (LDs). Acylglycerolphosphate acyltransferases (AGPATs), also known as lysophosphatidic acid acyltransferases (LPAATs), are a family of five enzymes that catalyze the conversion of lysophosphatidic acid (LPA) to phosphatidic acid (PA), the second step of the TAG biosynthesis pathway. PA, apart from its role as an intermediate in TAG synthesis, is also a precursor of glycerophospholipids and a cell signaling molecule. Although the different AGPAT isoforms catalyze the same reaction, they appear to have unique non-overlapping roles possibly determined by their distinct tissue expression and substrate specificity. This is best exemplified by the role of AGPAT2 in the development of type 1 congenital generalized lipodystrophy (CGL) and is also manifested by recent studies highlighting the involvement of AGPATs in the physiology and pathology of various tissues and organs. Importantly, AGPAT isoform expression has been shown to enhance proliferation and chemoresistance of cancer cells and correlates with increased risk of tumor development or aggressive phenotypes of several types of tumors.

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Lipid metabolism in cancer: New perspectives and emerging mechanisms

Cited by 294 publications

References 242 publications

Molecular response to PARP1 inhibition in ovarian cancer cells as determined by mass spectrometry based proteomics

Molecular response to PARP1 inhibition in ovarian cancer cells as determined by mass spectrometry based proteomics

A Novel Integrated Metabolism-Immunity Gene Expression Model Predicts the Prognosis of Lung Adenocarcinoma Patients

Lipid Metabolism in Cancer: The Role of Acylglycerolphosphate Acyltransferases (AGPATs)

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